Media articles often communicate the latest scientific findings, and readers must evaluate the evidence and consider its potential implications. Prior work has found that the inclusion of graphs makes messages about scientific data more persuasive (Tal & Wansink, 2016). One explanation for this finding is that such visualizations evoke the notion of "science"; however, results are mixed. In the current investigation we extend this work by examining whether graphs lead people to erroneously infer causation from correlational data. In two experiments we gave participants realistic online news articles in which they were asked to evaluate the research and apply the work's findings to a real-life hypothetical scenario. Participants were assigned to read the text of the article alone or with an accompanying line or bar graph. We found no evidence that the presence of graphs affected participants' evaluations of correlational data as causal. Given that these findings were unexpected, we attempted to directly replicate a well-cited article making the claim that graphs are persuasive (Tal & Wansink, 2016), but we were unsuccessful. Overall, our results suggest that the mere presence of graphs does not necessarily increase the likelihood that one infers incorrect causal claims. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

中文翻译：

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图表不会导致人们从相关性中推断出因果关系。

媒体文章经常传达最新的科学发现，读者必须评估证据并考虑其潜在影响。先前的工作发现，包含图表使有关科学数据的信息更具说服力（Tal & Wansink，2016）。对这一发现的一种解释是，这种可视化唤起了“科学”的概念。然而，结果好坏参半。在当前的调查中，我们通过检查图表是否会导致人们从相关数据中错误地推断出因果关系来扩展这项工作。在两个实验中，我们为参与者提供了现实的在线新闻文章，要求他们评估研究并将工作的发现应用于现实生活中的假设场景。参与者被分配单独阅读文章的文本或阅读随附的线或条形图。我们没有发现任何证据表明图表的存在会影响参与者将相关数据作为因果关系的评估。鉴于这些发现出乎意料，我们试图直接复制一篇被广泛引用的文章，声称图表具有说服力（Tal & Wansink，2016），但我们没有成功。总体而言，我们的结果表明，仅仅存在图表并不一定会增加推断错误因果主张的可能性。（PsycInfo 数据库记录 (c) 2022 APA，保留所有权利）。我们的结果表明，仅仅存在图表并不一定会增加人们推断出不正确的因果主张的可能性。（PsycInfo 数据库记录 (c) 2022 APA，保留所有权利）。我们的结果表明，仅仅存在图表并不一定会增加人们推断出不正确的因果主张的可能性。（PsycInfo 数据库记录 (c) 2022 APA，保留所有权利）。